Sr. Data Analyst (Product Analytics) in New York at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Data Analyst (Product Analytics) based in United States.

As a Senior Data Analyst, you will turn product and business data into actionable insights that shape product strategy, growth, and customer experience. You will work closely with Product, Engineering, Design, Marketing, and Leadership to define meaningful success metrics and evaluate business impact. The role combines hands-on product analytics with experimentation, funnel analysis, retention, segmentation, and monetization analysis. You will also help strengthen the organization’s analytics foundation by improving event tracking, data reliability, and access to trusted information. Your work will support better decision-making across teams and help identify opportunities for product and business growth. This is an impactful opportunity for an analytical, collaborative professional who thrives in a fast-moving environment.

• Partner with Product, Marketing, and Leadership teams to identify opportunities, influence product strategy, and support data-driven business decisions.
• Lead end-to-end product and growth analyses covering funnels, cohorts, retention, segmentation, monetization, user behavior, and experimentation.
• Define success metrics and assess the impact of new features, experiments, and broader product initiatives.
• Build dashboards, recurring reports, and self-service analytics that make insights accessible to stakeholders across the organization.
• Collaborate with Engineering to design, implement, validate, and maintain product event tracking within React-based interfaces.
• Identify, investigate, and resolve tracking issues that could affect data quality and analytical reliability.
• Combine data from multiple sources, including product analytics, advertising platforms, payment systems, and CRM systems, to develop a unified view of business performance.
• Document key metrics, tracking plans, and data definitions to establish consistent understanding across teams.
• Contribute to improvements in data pipelines, storage, and analytical frameworks where needed.

Requirements:

• Bachelor's degree or higher in a relevant field, or equivalent professional experience.
• 3+ years of experience in data science, data analytics, or another quantitative discipline, with a demonstrated record of delivering analytics projects.
• Strong experience in product analytics, experimentation, funnel analysis, retention, segmentation, and user behavior analysis.
• Experience with event-tracking instrumentation and close collaboration with Engineering teams to validate and maintain analytics implementations.
• Experience working with real-time and historical data, including data cleaning, processing, analysis, modeling, insight generation, and execution strategy.
• Strong proficiency with SQL and experience with statistical programming or analytical tools such as R or Python.
• Experience with product and marketing analytics platforms such as Amplitude and Google Analytics.
• Strong analytical, quantitative, and problem-solving skills with excellent attention to detail.
• Ability to communicate complex findings clearly through data visualization and compelling storytelling to both technical and non-technical audiences.
• Strong ownership, initiative, and follow-through, with the ability to thrive in a startup or fast-paced environment.
• Experience improving data pipelines, data storage, or analytical frameworks is preferred.
• Familiarity with event-tracking technologies such as JavaScript or Google Tag Manager is a plus.

Benefits:

• Compensation and benefits details were not specified in the source job description.
• Opportunity to influence product strategy, growth, and customer experience through data.
• Cross-functional collaboration with Product, Engineering, Design, Marketing, and Leadership teams.
• Exposure to product analytics, experimentation, growth analytics, and modern data infrastructure.
• Opportunity to improve analytics foundations, event tracking, and organizational data accessibility.
• Fast-paced environment with significant ownership and opportunities to contribute to business decisions.